Injury risk prediction for traffic accidents in Porto Alegre/RS, Brazil

TL;DR

This paper applies machine learning to predict injury risk in traffic accidents using data from Porto Alegre, Brazil, identifying key factors that contribute to injury outcomes.

Contribution

It introduces a novel application of machine learning models for injury risk prediction in traffic accidents using publicly available data.

Findings

Identified key attributes influencing injury risk.

Developed predictive models with promising accuracy.

Provided insights into accident factors leading to injuries.

Abstract

This study describes the experimental application of Machine Learning techniques to build prediction models that can assess the injury risk associated with traffic accidents. This work uses an freely available data set of traffic accident records that took place in the city of Porto Alegre/RS (Brazil) during the year of 2013. This study also provides an analysis of the most important attributes of a traffic accident that could produce an outcome of injury to the people involved in the accident.